Linear System Identification Under Multiplicative Noise from Multiple Trajectory Data
Linear System Identification Under Multiplicative Noise from Multiple Trajectory Data
复制标题
多轨迹数据乘性噪声下的线性系统辨识
DOI：
10.23919/acc45564.2020.9147756
复制
发表时间：
2020
期刊：
影响因子：
--
通讯作者：
T. Summers
中科院分区：
文献类型：
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作者：
Yu Xing;Benjamin J. Gravell;Xingkang He;K. Johansson;T. Summers
乘性噪声模型的研究在控制理论中有着悠久的历史，但在复杂网络系统和基于学习的控制系统的背景下重新出现。我们考虑线性系统的识别与乘性噪声从多个状态输入轨迹数据。我们提出了探索性的输入信号沿着与最小二乘算法同时估计标称系统参数和乘性噪声协方差矩阵。通过分析系统的一阶和二阶矩动力学，证明了最小二乘估计的渐近相合性。数值模拟的结果表明。
The study of multiplicative noise models has a long history in control theory but is re-emerging in the context of complex networked systems and systems with learning-based control. We consider linear system identification with multiplicative noise from multiple state-input trajectory data. We propose exploratory input signals along with a least-squares algorithm to simultaneously estimate nominal system parameters and multiplicative noise covariance matrices. The asymptotic consistency of the least-squares estimator is demonstrated by analyzing first and second moment dynamics of the system. The results are illustrated by numerical simulations.
具有随机系统惯量的低惯量电网的性能和稳定性分析
DOI：
10.23919/acc.2019.8814402
发表时间：
2019
期刊：
American Control Conference
影响因子：
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作者：
Guo, Yi;Summers, Tyler H.
通讯作者：
Summers, Tyler H.